Use LLM for python code acceleration (week 4 exercise)

week4/community-contributions/tsungyulin_code_accelerate/config.py

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+OPENAI_MODEL = "gpt-4o-mini"
+CLAUDE_MODEL = "claude-3-5-haiku-20241022"
+
+OUTPUT_MAX_TOKEN = 2000
+
+PYTHON_CODE = '''
+import math
+
+def pairwise_distance(points_a, points_b):
+    """
+    Compute the pairwise Euclidean distance between two sets of 3D points.
+
+    Args:
+        points_a: list of (x, y, z)
+        points_b: list of (x, y, z)
+    Returns:
+        A 2D list of shape (len(points_a), len(points_b)) representing distances
+    """
+    distances = []
+    for i in range(len(points_a)):
+        row = []
+        for j in range(len(points_b)):
+            dx = points_a[i][0] - points_b[j][0]
+            dy = points_a[i][1] - points_b[j][1]
+            dz = points_a[i][2] - points_b[j][2]
+            d = math.sqrt(dx * dx + dy * dy + dz * dz)
+            row.append(d)
+        distances.append(row)
+    return distances
+
+
+# Example usage
+if __name__ == "__main__":
+    import random
+    points_a = [(random.random(), random.random(), random.random()) for _ in range(100)]
+    points_b = [(random.random(), random.random(), random.random()) for _ in range(100)]
+    dists = pairwise_distance(points_a, points_b)
+    print(f"Distance[0][0] = {dists[0][0]:.4f}")
+'''